The present invention is directed to a method for detecting road users and obstacles on the basis of camera images, and to a device for detecting road users and obstacles on the basis of camera images.
By detecting an imminent collision between a road user and the vehicle of an observer at an early stage, one can improve the safety of vehicle occupants as well as of the potential other party involved in the collision. The time savings that can be gained by visually detecting and evaluating the observable region in front of the observer's vehicle permits stepped reactions of the vehicle occupant safety systems (e.g., a gentle firing of the airbag), or makes reactions possible in the first place to protect the other party in a collision (such as raising the engine hood in the case of collision involving a pedestrian). Developments culminating in switchable crash structures have made it more important than ever to know the type of other party involved in the accident (truck, passenger car, motor cycle, pedestrian).
Current developments in precrash sensors are directed, inter alia, to the analysis of methods based on infrared lasers, ultrasound, or radar sensors. The drawbacks of these systems are due, in part, to their limited range (ultrasound, infrared laser) and to their inability to identify the other party potentially involved in a collision, along the lines of a reliable type classification (truck, passenger car, motor cycle, person). In radar-based systems, inter alia, non-metallic objects (e.g.: people or trees) are not able to be reliably detected by inexpensive sensors suited for use in vehicle applications. However, adapting an optimally stepped reaction of safety systems to imminent collisions requires reliable detection and dependable typing. Within the framework of such a stepped reaction, for example in the event of a collision with a pedestrian, active measures should be taken to ensure the pedestrian's safety. In this connection, one can conceive of rapid changes in the vehicle body form to minimize the probability of serious head or leg injuries. However, the basic condition for activating these measures is that the safety system be able to reliably detect road users and classify them according to type (e.g.: passenger car, truck, bicycle riders, pedestrians).
Generally, methods for interpreting image scenes endeavor to not only obtain purely two-dimensional image information, but multi-dimensional scene information as well. They do so already in the first step, using a mostly costly sensor (stereo sensor or high-resolution radar or lidar). In order to detect objects, these methods are based, however, on models, above all with respect to the position and orientation of potential targets, as well as with respect to a predefined, fixed geometry of the orientation to the sensor and surroundings. In practice, it is often ascertained, however, that these models and assumptions frequently do not conform with actual conditions, so that misinterpretations result.